Machine Learning Researcher, Audio
$200,000 – 250,000+, Equity + Bonus
Remote (US & Europe) / San Francisco, CA (Hybrid preferred)
Full-time / Permanent

DeepRec has partnered with a fast-growing, revenue-generating voice AI company empowering enterprises to build AI phone agents at scale. Recent Series C funding with backing from leading Silicon Valley investors, they are building the models and infrastructure that make voice the primary interface between businesses and their customers.

This company has built all of their current models completely in-house, and every model ships to real, paying customers almost immediately. No speculative research track here. If you want your work to hit production within weeks, not years, this is that role.

The Opportunity

The research team are working toward a single, ambitious goal: a fully speech-to-speech conversational AI model that understands and responds like a human, in real time. You'll work across the core building blocks of that roadmap, such as: speech-to-text, text-to-speech, neural audio codecs, and getting LLMs to understand and reason over audio directly.

You'll take ideas from theory through large-scale training to production inference serving millions of calls a day, working closely with engineering and product teams to get your research into real customer environments fast.

What You'll Do
  • Build TTS models that sound natural, expressive, and human
  • Build STT systems that stay accurate with accents, background noise, and messy phone lines
  • Work on neural audio codecs, compressing audio efficiently without losing quality
  • Explore LLM-Audio Understanding
  • Prepare and manage large audio datasets, and design how models are trained on them
  • Run training across many GPUs at once, keeping an eye on cost and speed
  • Run fast, well-designed experiments to test what actually works
  • Make sure models run fast and reliably in production, not just in benchmarks

What You'll Bring
Essential
  • A genuine, self-driven interest in this area of research, shown through your own projects or papers, not just what a past employer asked you to do
  • Hands-on experience building or improving TTS, ASR, speech-to-speech, or neural audio codec systems
  • A track record of original, hands-on technical work, rather than off-the-shelf tools or common tutorial-style projects
  • Strong Python skills and experience training or running large models
  • Comfortable working autonomously 
Desirable
  • Experience getting LLMs to understand or reason about audio - the team's top priority right now
  • Experience with model distillation
  • Experience fine-tuning or training language or speech models with reinforcement learning
  • Published research or open-source work in speech or language AI
  • Background working with real-time speech systems or phone-based systems
  • A PhD is welcome but not required. Strong, independent work matters more than qualifications
We encourage you to apply even if you don't meet every requirement. The right mindset and genuine curiosity matter as much as the resume.

What's In It For You
  • Ground-floor seat in a lean and growing research team with real scope to shape it as it scales
  • Every research output ships to real customers, no long speculative research projects
  • High autonomy to shape your own research direction, tooling, and (for senior hires) the team itself
  • Work across ASR, TTS, neural codecs, and the frontier of LLM-audio understanding & speech-to-speech modelling
  • Well-capitalised, fast-moving environment without big-lab bureaucracy
  • Healthcare, dental, vision, meaningful equity, and every tool you need to succeed
  • Remote-friendly across the US